A MULTI-LEVEL ORGANIZATIONAL SYSTEM ENGINEERING FRAMEWORK FOR MANAGING REGIONAL SECURITY AND RESILIENCE Текст научной статьи по специальности «Компьютерные и информационные науки»

УДК 004.94

doi:10.21685/2307-4205-2022-4-15

A MULTI-LEVEL ORGANIZATIONAL SYSTEM ENGINEERING FRAMEWORK FOR MANAGING REGIONAL SECURITY AND RESILIENCE

A.V. Masloboev1, V.N. Tsygichko2

1 Putilov Institute for Informatics and Mathematical Modeling of the Federal Research Centre «Kola Science Centre of the Russian Academy of Sciences», Apatity, Russia 2 Federal Research Centre "Computer Sciences and Control" of the Russian Academy of Sciences, Moscow, Russia

1 masloboev@iimm.ru, 2 vtsygichko@inbox.ru

Abstract. Background. The study is aimed at the development of general theory and methodology of synthesis and analysis of the multi-level organizational management structures for the efficiency enhancement of distributed control of the regional socio-economic system security and resilience. The final solution to this urgent problem in terms of application universality in relation to the subject field under study due to its dynamism and interdisciplinary nature has not yet been found. Materials and methods. The problem statement and the proposed formal approach to synthesis of organizational structures are based on the general system theory, control theory, theory of hierarchical multi-level systems, decision theory, methods of system analysis and multi-agent modeling of complex systems. Results and conclusions. The fundamentals of developed theory of organizational structure synthesis for managing socioeconomic systems of various classes and scales are considered. Methodological and software tools for synthesis automation of the multi-level organizational structure models generated for management support of regional security under conditions of resilience loss of regional critical infrastructures have been developed. The target application of the developments is focused on functioning information and analytical maintenance of situational centers in the region and operation support of the regional security control systems.

Keywords: synthesis, organizational structure, situational control, modeling, multi-level system, regional security, resilience

Acknowledgments: the work was carried out within the framework of the State Research Program of the Putilov Institute for Informatics and Mathematical Modeling (project No. FMEZ-2022-0023).

For citation: Masloboev A.V., Tsygichko V.N. A multi-level organizational system engineering framework for managing regional security and resilience. Nadezhnost' i kachestvo slozhnykh sistem = Reliability and quality of complex systems. 2022;(4): 143-152. (In Russ.). doi:10.21685/2307-4205-2022-4-15

СРЕДСТВА СИНТЕЗА МНОГОУРОВНЕВЫХ ОРГАНИЗАЦИОННЫХ СИСТЕМ ДЛЯ УПРАВЛЕНИЯ РЕГИОНАЛЬНОЙ БЕЗОПАСНОСТЬЮ И УСТОЙЧИВОСТЬЮ

А. В. Маслобоев1, В. Н. Цыгичко2

1 Институт информатики и математического моделирования имени В. А. Путилова Федерального исследовательского центра «Кольский научный центр Российской академии наук», Апатиты, Россия 2 Федеральный исследовательский центр «Информатика и управление» Российской академии наук, Москва, Россия 1 a.masloboev@ksc.ru, 2 vtsygichko@inbox.ru

Аннотация. Актуальность и цели. Работа направлена на развитие общей теории и методологии синтеза и анализа многоуровневых организационных структур для повышения эффективности распределенного управления безопасностью и устойчивостью региональных социально-экономических систем. Окончательное решение этой актуальной задачи с точки зрения универсальности применения в отношении к исследуемой предметной области еще пока не найдено, что обусловлено ее динамичностью и междисциплинарным характером. Материалы и методы. Постановка задачи и предлагаемый формальный подход к синтезу организационных структур базируются на общей теории систем, теории управления, теории иерархических многоуровневых систем, теории принятия решений, методах системного анализа и мультиагентного моделирования сложных систем. Результаты и выводы. Рассмотрены основополагающие принципы развиваемой теории синтеза организационных структур управления социально-экономическими системами различного класса и мас-

© Маслобоев А. В., Цыгичко В. Н., 2022. Контент доступен по лицензии Creative Commons Attribution 4.0 License / This work is licensed under a Creative Commons Attribution 4.0 License.

штаба. Разработан методический и программный инструментарий автоматизации синтеза моделей многоуровневых организационных структур для управления региональной безопасностью в условиях потери устойчивости функционирования критических инфраструктур региона. Применение разработок ориентировано на информационно-аналитическое сопровождение работы ситуационных центров региона и систем обеспечения региональной безопасности.

Ключевые слова: синтез, организационная структура, ситуационное управление, моделирование, многоуровневая система, региональная безопасность, устойчивость

Финансирование: работа выполнена в рамках государственного задания ИИММ КНЦ РАН (НИР № FMEZ-2022-0023).

Для цитирования: Маслобоев А. В., Цыгичко В. Н. Средства синтеза многоуровневых организационных систем для управления региональной безопасностью и устойчивостью // Надежность и качество сложных систем. 2022. № 4. С. 143-152. doi:10.21685/2307-4205-2022-4-15

Introduction

Synthesis of multi-level organizational structures for managing socio-economic systems is and will be in the near-term outlook one of the most urgent fundamental interdisciplinary problems of the state-of-the-art control sciences. Chances for success in attaining organizational system goals significantly rely on the performance and capabilities of its management structure. Nowadays, when the geopolitical situation in the world is unpredictably changing with an increasing rate problems concerning formal synthesis, analysis and dynamic configuration of multi-level organizational management structures come to the foreground. Especially acute, these issues arise in matters of defense and national security ensuring agenda in accordance with systematics [1, 2]. Generation and implementation of reasonable organizational management structures relevant to the current situation predetermine the efficiency of decision-making under security and resilience control of socio-economic system critical infrastructures.

For the first time, the general ideas and original theoretical formulations of hierarchical organizational structure synthesis for security issues and applications were announced by Prof. Vitaly N. Tsygichko and Alexandra Yu. Popovich in Sofia, Bulgaria more than ten years ago. Their presentation on this challenging research topic at 7th International scientific and practical conference "The latest achievements of European science" gathered a great discussion, but, however, did not get further development in foreign safety scientific society. Thus, organizational and technological issues were passed off without due attention. Currently, there is a surge of interest to these studies both abroad, and in the domestic research.

The state-of-the-art foundations of the formal theory of organizational management structure synthesis are based on a wide range of various studies that reveal features of real control actors and multi-level entities (organizations). First of all, there are fundamental research works [3-6] which generalizing the synthesis principles into a unified conception and providing a rich empirical data to formal synthesis procedure implementation. However, so far there is no well-grounded and valid methodology for synthesis of organizational management structures applied to real security control applications, specifically, in socio-economic sphere. There is practically nothing that can provide us with comprehensive information and analytical decision-making support tools. Existing formal theories are for the most part focused on an analysis of hypothetical idealized management structures with formal inter-element relations given and are rather alienated from the studies of real organizational systems and applications [7, 8]. The main problem and the cause of most failures is the absence of formal procedures and basic parameters that determine organizational management structure generation. Without an explicit definition of these parameters and consistent model representation of management structures it is impossible to develop a reasonable methodology for multi-level organizational system engineering as to security control and other topical applications.

Then, in this study we are going to remind a formal approach to synthesis of organizational management structures and present its software implementation for regional security and resilience management support of socio-economic systems. We propose an advanced synthesis methodology which derives from fundamental axioms and principles of systems analysis, decision and control theory and is based on the feature examination of multi-level organizational systems, those genesis and operation.

Materials and methods

Regional security control process structuring consists in generation of hierarchical entity network with interlinked subsystems. A control subsystem can be defined as a multi-level structure consisting of in-

terlinked subsystems the elements of which are empowered to make decisions. The subsystems and elements form a hierarchy. Higher level element states a problem to a lower-level element and influences it by changing problems, introducing limitations or restrictions, or enumerating alternative actions. A low-level element is free in its actions in executing assigned tasks within the framework of specified restrictions or alternatives. A higher-level element organizes interaction of elements (subsystems) subordinated to it for the purpose of achieving goals (performing tasks) assigned to it by a higher-element. A lower-level element influences a decision by a higher-level element by informing it on its state and the consequences of the decision it makes. A higher-level element can correct or alter its decision in conformity with this information. Thus, there occurs coordination of lower-level decisions with the goals of the entire organizational system used for managing the regional security.

The informational structure of the hierarchical control subsystem in question reflects the hierarchic nature of the organizational system. In an actual control subsystem this is reflected in the fact that a specific level of description of system state corresponds to each control component. Higher-level control elements deal with larger subsystems and broader aspects of system activity. Description of system state at higher levels is less detailed than at lower ones, while the problems resolved at higher levels contain more uncertainty and are more difficult to solve.

Formally, control bolls down to coordination of the activities of lower-level subsystems, which in practice is accomplished by setting and defining problems for subsystems of all levels. Defining problems to be solved by higher-level elements takes place in the language of the parameters of these elements, which essentially gives certain freedom in choosing of control parameters for lower-level elements. The temporal structure of control system functioning is also heterogeneous. The higher the level of control is, the greater the period of decision-making and the overall duration of execution of assigned tasks are. The enumerated properties of interlevel relations determine substantially the functioning nature of the control system as a hierarchical or network-centric organizational structure.

Incomplete information on the situation developing at any given moment in the activities of target systems is one of the principal features of processes in these systems. This means that decision-making in all control components takes place in conditions of a different degree of uncertainty, which substantially affects the quality of decisions and, consequently, the course of functioning processes.

Then, we are going to examine this aspect in a more detailed way. Decision-making is based on a

goal-oriented process of uncertainty resolution. Precise values of decision-targeted parameters (j = 1, J) are

rarely known, but decision maker can always operate ranges of possible values (lj).

For each decision there exists an allowable accuracy of input information, i.e. minimal allowable

ranges of decision-targeted parameters - 5j. Specification of 5j for all j = 1, J defines allowable region of

uncertainty A = { 5j } . Introduction of allowable range of accuracy makes it possible to convert a continuous set of numerical values of state description parameters to a bounded finite set and to perform practical calculations. Let the allowable ranges of accuracy 5j be determined for all parameters je J of description

of a certain social entity, and let the ranges of determination of these parameters lj e L be known

(where L is the region of determination of the state of the target entity. We shall divide the ranges of possible values of components lj of vector L into segments of length 5j. There will be Nj segments in each

interval:

l,

N, =j. (1)

j 5.

The probability that the numerical value of parameter j will fall within the kj segment, kj = 1, N., shall be designated Pk . Then, by virtue of the independence of components of vector L , full entropy of decision will be written as:

J N

Ef =-ZZPkj logPj. (2)

j =1 kj =1

Analytical process of uncertainty resolution that constitutes the core of decision-making is directed on reduction of initial region L to a certain final region, i.e. reduction if initial entropy Ein (full entropy at the begin-

ning of the decision-making process) to residual entropy Er (full entropy at the end of the process). Entropy approach allows us to introduce quality of decision as a function of uncertainty resolution degree:

where T is time given for the certain decision-making; sup Er determines the degree of risks the decisionmaker takes if he makes a decision at the moment T .

The most effective process of uncertainty resolution is based on the principle of sequential resolution of uncertainty. This principle states that the process of systems analysis should consist in movement from determination of the goals and conditions of organizational system development as an integral entity toward determination of objectives, mechanisms of functioning, conditions and criteria in detail and for each subsystem and element. In the process of this movement, at each level of system representation, beginning with the highest level, one selects for further examination from the many possible development alternatives only those which merit attention from the standpoint of system goals, while the remainder are discarded and no longer considered. Correctness of selection of alternatives at each level of synthesis is verified by means of analyzing them at a lower, more detailed level of representation. The initial alternatives are refined based on the results of this analysis, and their number is reduced. Such organization of analytic process makes it possible to isolate for analysis only a small portion of the infinite number of possible sets of parameters values and to determine the most rational ones from this limited number of alternatives.

Thus, the principle of uncertainty sequential resolution expects the implementation of an iterative analysis procedure, downward through the hierarchy of descriptions of the organizational system, whereby one can avoid consideration of the complete set of development alternatives. The mechanisms of synthesis and detailing serve as the implementation tool of this procedure. These mechanisms ensure description informational fullness and integrity of multi-level organizational systems. Introduction of measure, which reflects the requisite degree of description aggregation of the system and its elements at different levels of generalization, is one possible way of constructive continuation of the principle of uncertainty sequential resolution. A complexity threshold [9] can be adopted as such a measure.

The procedure of systems analysis, organized with observance of the principle of uncertainty sequential resolution, constitutes a certain invariant of the thought process. It is therefore natural that a constructive form of representation of this process is linked first and foremost with the properties of thinking. Such features of thought process as ability of purposeful multi-level abstract reflection of reality, ability to classify and other, involve one of its most important properties - limitedness of the number of factors and conditions with which decision-maker consciousness can operate simultaneously in solving any problem. These properties are being actively studied at the present time, and the indices of this limitation are extensively used in practice.

In decision-making theory complexity threshold is a measure of allowable dimensionality of problem which could be solved in a given period of time. Complexity threshold obeys to the following axioms:

1) a specific complexity threshold corresponds to every specific problem;

2) complexity threshold is a non-decreasing function of time given for the problem-solving.

The introduced above complexity threshold and decision quality concepts allow us to advance a mathematical formulation for synthesis of organizational management structures.

Let r{y,i} be a graph that represents the management structure of the given organizational system, and let the following function be given:

The goal is to find a graph r{y,i} where function (4) finds its minimum on conditions that

xiT)=i - ,

(3)

(4)

X*Xa (or supEr <Ea ) and

i

i

IEL* ET=I*=11, EL * К

(5)

г

E = IEY < E

(6)

Y

where %a - admissible quality of control problem solution; Er - admissible uncertainty resolution degree (for the control problem); i - the ordinal number of problem in the sequence of problems being solved at the y stage of decision-making process; I - the number of such problems; E"'p - a priory entropy for the

Y stage of decision-making process; E~p - a priory entropy for the y stage of decision-making process; Ey - complexity threshold; T - the management cycle of the organizational system.

If the management cycle of organizational system is given a priori or is determined by technological process, then the synthesis problem could be formulated in the following way: search a control structure that satisfies the conditions (5) and (6):

r|Y,i} = r(T, Ep, [El}, x), (7)

Synthesis of organizational management structures is one of the most complicated problems control theory and system theory have. Construction of functions (4) and (7) as well as calculation of complexity threshold for particular control problems arise the main difficulties.

The synthesis process cannot be determined by any general optimization scheme. This means that functions (4) and (7) are iterative procedures with human decisions involved at each step. These procedures could be described by algorithmic functions only. Our goal is in finding the algorithmic functions that approximate real processes in the most accurate manner. Principle of uncertainty sequential resolution will help us ones again, namely, from the start by modeling general features of the process until operation on determination of precise details.

Our study of real organizational system genesis analysis has resulted in extraction of two main parameters that determine organizational management structures. These parameters are conditionally defined as "complexity" (c) and "payload" (p). We must underline that each of these parameters has a complicated inner structure, and takes different forms in different organizational systems. Let us illustrate these parameters by a simple example. What kind of problems do we consider to be difficult? For example, typing. It seems to be a very easy problem. Every user of computer can do that. However, if we need to type several hundreds of pages in a couple of hours, we think it to be impossible. On the other hand, some mathematical problem. Let it be one of the problems that take about 5 minutes from a specialist to solve it, and let its solution fit in one page. However, a person who doesn't have any qualification in mathematics would not be able to solve it, even if he has a lot of time in his hands. This example illustrates two sides of difficulty. We define these sides "complexity" (it causes the sort of difficulties illustrated by the second example) and "payload" (this is what we run across in the first example).

An employee i, who is assigned to a certain problem h, has to have enough time to be able to deal with the problem payload ph and enough qualification to deal with its complexity ch. It is convenient to

handle sort of limit-parameters: complexity limit ci as the maximum complexity of problem the employ*

ee i can deal with, and payload limit p as the maximum amount of time he can spare. Ability or inability

p c

to solve a problem is determined not by the problem's ch and ph, but by the ratios —, — .

pr cr

We must underline that the meaning and inner structure of the parameter complexity differs between problems of different types. For example, if we consider problems for security department, we bring to the fore requirements on tactical training and physical fitness. On the other hand, if we analyze work of sales department, we are much more interested in the abilities of employees to deal with customers. The more uncertainty of the problems solved is, the more significant analytical and creative abilities of the employee are.

For the general case we can consider a set of types of problems (or specializations) urgent for the certain organizational system. For each of the type we must construct an independent gradation of complexity. Each level at each specialty has its own meaning. In other words, c = c(5), s e S , where S - is a set of

specializations urgent for the examined organizational system.

Let us introduce a function of expected effectiveness Qh r, which reflects the quality of problem solution a manager can expect, if he entrusts employee c with problem h .

At the current stage of approach, we propose the following approximation:

Qh, i = QC , • QP, • QMi>, (8)

where QC i =П fc

Л=1

.(л)

is a term representing the contribution of "complexity"; Z is a number of spe-

Í

cialization urgent for the organizational management system; Qphi = f

f b, \ Zph

M_

P*

is a term representing the

V /

contribution of "payload"; bi is a number of problems the employee i is entrusted with at the current cycle of the system functioning; QM{ is a term that approximates manager contribution to the problem-solving, which reflects such manager functions as setting problems, consulting support, control, etc.

Results and Discussion

To mitigating the consequences of critical situations in the regional socio-economic systems, it is necessary to provide prompt and effective managerial decision-making in a extremely limited time. This fact stipulates a need for transition to the network-centric control model in managing the regional security and resilience. The network-centric approach most sufficiently reflects the real nature of regional socioeconomic system management and takes into account the decentralized nature of regional security ensuring processes both in terms of its functional structure and the control actor membership. Regional security network-centric control implies a network structure of organizational management with dedicated control centers development. The interaction between these control centers should be carried out on the basis of it integration into a unified regional information space. For the implementation of regional security network-centric control model and efficiency enhancement of the decentralized decision-making the generation and synthesis of virtual problem-oriented organizational management structures in each domain of regional security should be provided within the distributed information environment covering all the critical infrastructures of regional socio-economic system. For these purposes, the fundamentals of organizational structure synthesis general theory [10] briefly presented above and applicable synthesis method [11] of multi-agent models of the virtual network-centric multi-level organizational structures for managing regional security and resilience have been developed. The synthesis methodology of hierarchical and network-centric organizational management structures is implemented within the framework of software tooling system "OS-Synthesizer" used for various practical applications in the field of modeling, analysis and engineering of complex organizational systems.

The software system corresponds an integrated multi-agent modeling environment of control problems and management processes for ensuring the regional security and critical infrastructure resilience. OS-Synthesizer is an application toolset providing the automated synthesis and analysis of organizational management structure models intended for information support and coordination of the decentralized managerial decision-making in the field of regional security. The system allows execution of the combined formal synthesis and efficiency analysis procedures under generating and configuring of the organizational management structure models subject to the specificity of control problem solving both in automatic and interactive mode. OS-Synthesizer provides dynamic pattern-driven formation of these models composition also, as well as the adaptive tuning of model characteristics under changing external environment. In turn, this contributes to the design process automation of the organizational management structures, well-posed sampling and composition of their elements under given conditions and restrictions on the set of problems to be solved. The multi-agent system technology [12] was used as a toolkit for the implementation of OS-Synthesizer system.

OS-Synthesizer has a modular architecture and includes the following main functional units discussed in detail in earlier study [13]:

1) organizational management structure (OS) model synthesis unit;

2) OS-model generation and configuration unit;

3) OS-model analysis and efficiency assessment unit;

4) OS-model tuning and reconfiguration unit;

5) OS-model optimization and development unit;

6) multi-agent simulation environment engine unit.

The generic enlarged structure of the OS-Synthesizer software system is shown in Figure 1.

Fig. 1. The generic architecture of the OS-Synthesizer software tooling system

The OS-Synthesizer software system also includes some extra tools for designing conceptual (cognitive, semantic, ontological, etc.), dynamic and agent-based models intended for simulation of various scenarios of the regional security control and critical situations development. These models are as well used within the efficiency analysis of the alternative organizational management structures synthesized to preventing and counteracting critical situations accordingly to simulated scenarios. Such tools allow implementing the automated synthesis of organizational management structure models based on the use of a library of typical models and modeling patterns. In addition, OS-Synthesizer functionality provide correctness analysis of the synthesized models, aggregation of several models into a common polymodel complex, coordination of simulated time quantization for various submodels (normalization of models in time), interpretation of simulation data and results visualization in text, tabular or graphic form, export of generated analytical information and reports to monitoring information systems of regional situational centers.

The conceptual schemes of the OS-Synthesizer principal units are shown in Figure 2 and Figure 3.

Fig. 2. The structure of the OS-model generation and editing unit (adopted from [14])

Fig. 3. The structure of the OS-model aggregation and tuning unit

OS-Synthesizer supports three modes for model generation of organizational management structures: direct, inverse and bidirectional synthesis, differing in the fixed goal, initial data and halt conditions of the iterative synthesis method. In general, the system maintains analysis and synthesis of various type organizational management structures both hierarchical [10, 15] and network-centric [16, 17]. OS-Synthesizer provides operation with all necessary information for multi-agent model generation, evaluation and reconfiguration of the organizational management structures to regional security control subject to the specification and operational (applied) context of critical situations.

The field of application of the OS-Synthesizer system as a tool for information support of regional security and resilience management is determined by providing the capability of synthesis and analysis of such classes of the organizational management structures as simple, adhocratic, bureaucratic, divisional and others oriented to operate both in stable and dynamic open environment characterized by a high level of uncertainty.

OS-Synthesizer software system was approved in real applications, particularly, for practical problem-solving in the field of situational control of economic security of the Murmansk region by integrating it as a part into information and analytical system "Prognosis" used by the Ministry of economic development and the Governor situational center of the Murmansk region.

Conclusion

The principal approach and formal basis proposed in this study has given an impulse to further development of the general theory of organizational system synthesis along the line of network-centric model generation of management structures to situational control the regional security and resilience. This theory is based on the entire methodology, which is applicable for synthesis of organizational management structures, and operates with a wide range of control methods and decision-making support tools for engineering, analysis and reconfiguration of various organizational management structures. Discussed theoretical fundamentals and methods resulted to development and application of the software tooling system OS-Synthesizer.

Technologically, the system has a multi-agent implementation and contributes the combined automated synthesis, dynamic reconfiguration and performance evaluation of the organizational management structure models for supporting the network-centric control of regional security under emergency situations in regional critical infrastructures of socio-economic systems. OS-Synthesizer features are provided at the expense of the interaction of autonomous software agents and the use of simulation toolset framework.

Our developments can be efficiently used for decision-making information and analytical support in the regional situational centers as well as for analyzing the behavior dynamics of the security actors in various critical situations and coordinating their joint activities within the bounds of operational management and strategic planning of anti-crisis measures in the regional security control systems. The innovation potential of the OS-Synthesizer is focused on solving new practical problems in such interdisciplinary security ensuring domains as critical infrastructure resilience of regional socio-economic systems, environmental safety and personnel sustainability of the region.

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Информация об авторах / Information about the authors

Андрей Владимирович Маслобоев

доктор технических наук, доцент, ведущий научный сотрудник, заведующий лабораторией информационных технологий управления региональным развитием, Институт информатики и математического моделирования имени В. А. Путилова Федерального исследовательского центра «Кольский научный центр Российской академии наук» (Россия, г. Апатиты, ул. Ферсмана, 14) E-mail: masloboev@iimm.ru

Виталий Николаевич Цыгичко

доктор технических наук, профессор, главный научный сотрудник, Институт системного анализа Федерального исследовательского центра «Информатика и управление» Российской академии наук (Россия, г. Москва, пр-т 60-летия Октября, 9) E-mail: vtsygichko@inbox.ru

Andrey V. Masloboev

Doctor of technical sciences, associate professor,

leading researcher, head of the laboratory

of information technologies

for regional development management,

Putilov Institute for Informatics and Mathematical

Modeling of the Federal Research Centre

"Kola Science Centre of the Russian Academy of Sciences"

(14 Fersmana street, Apatity, Russia)

Vitaliy N. Tsygichko

Doctor of technical sciences, professor, chief researcher, Institute for system analysis, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences (9 60-letiya Oktyabrya avenue, Moscow, Russia)

Авторы заявляют об отсутствии конфликта интересов / The authors declare no conflicts of interests.

Поступила в редакцию/Received 19.05.2022 Поступила после рецензирования/Revised 21.06.2022 Принята к публикации/Accepted 18.07.2022